Topic 1 Question 229
You currently use a SQL-based tool to visualize your data stored in BigQuery. The data visualizations require the use of outer joins and analytic functions. Visualizations must be based on data that is no less than 4 hours old. Business users are complaining that the visualizations are too slow to generate. You want to improve the performance of the visualization queries while minimizing the maintenance overhead of the data preparation pipeline. What should you do?
Create materialized views with the allow_non_incremental_definition option set to true for the visualization queries. Specify the max_staleness parameter to 4 hours and the enable_refresh parameter to true. Reference the materialized views in the data visualization tool.
Create views for the visualization queries. Reference the views in the data visualization tool.
Create a Cloud Function instance to export the visualization query results as parquet files to a Cloud Storage bucket. Use Cloud Scheduler to trigger the Cloud Function every 4 hours. Reference the parquet files in the data visualization tool.
Create materialized views for the visualization queries. Use the incremental updates capability of BigQuery materialized views to handle changed data automatically. Reference the materialized views in the data visualization tool.
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A seems right but whats wrong with option D, can anybody please explain?
👍 4Jordan182024/01/05- 正解だと思う選択肢: A
Precomputed Results: Materialized views store precomputed results of complex queries, significantly accelerating subsequent query performance, addressing the slow visualization issue. Allow Non-Incremental Views: Using allow_non_incremental_definition circumvents the limitation of incremental updates for outer joins and analytic functions, ensuring views can be created for the specified queries. Near-Real-Time Data: Setting max_staleness to 4 hours guarantees data freshness within the acceptable latency for visualizations. Automatic Refresh: Enabling refresh with enable_refresh maintains view consistency with minimal maintenance overhead. Minimal Overhead: Materialized views automatically update as underlying data changes, reducing maintenance compared to manual exports or view definitions.
👍 1e70ea9e2023/12/30 - 正解だと思う選択肢: A
- Materialized views in BigQuery precompute and store the result of a base query, which can speed up data retrieval for complex queries used in visualizations.
- The max_staleness parameter allows us to specify how old the data can be, ensuring that the visualizations are based on data no less than 4 hours old.
- The enable_refresh parameter ensures that the materialized view is periodically refreshed.
- The allow_non_incremental_definition is used for enabling the creation of non-incrementally refreshable materialized views.
👍 1raaad2024/01/04
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